|Publication number||US6577329 B1|
|Application number||US 09/257,200|
|Publication date||Jun 10, 2003|
|Filing date||Feb 25, 1999|
|Priority date||Feb 25, 1999|
|Publication number||09257200, 257200, US 6577329 B1, US 6577329B1, US-B1-6577329, US6577329 B1, US6577329B1|
|Inventors||Myron Dale Flickner, David Bruce Koons, Qi Lu, Paul Philip Maglio, Carlos Hitoshi Morimoto, Edwin Joseph Selker|
|Original Assignee||International Business Machines Corporation|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (18), Non-Patent Citations (24), Referenced by (227), Classifications (10), Legal Events (6)|
|External Links: USPTO, USPTO Assignment, Espacenet|
The present application is related to U.S. patent application Ser. No. 09/257,208, filed on Feb. 25, 1999, to Dryer et al., entitled “METHOD AND SYSTEM FOR REAL-TIME DETERMINATION OF A SUBJECT'S INTEREST LEVEL TO MEDIA CONTENT”, assigned to the present assignee, and incorporated herein by reference.
The present invention generally relates to a display, and more particularly to a display with eye-tracking for judging relevance, to a user, of information being displayed on the display in a “ticker-like” fashion, and a method therefor.
With the explosive growth of digital cyberspace, “ticker-like” displays have recently emerged as one of the dominant user interfaces for Internet-based information systems.
Ticker displays are particularly useful for displaying highlights for a large variety of frequently updated information, such as stock quotes, sports scores, traffic reports, headline news, etc.
Typically, a ticker display uses an area of a computer screen to scroll text and/or image items continuously in a predetermined pattern (e.g., from left to right, from bottom to top, etc.). These are widely used by webcasting or Internet push systems, such as PointCast. Further, ticker displays have also been deployed by many popular websites such as MyYahoo, ESPN Sports Zone, and ABC News for similar purposes.
However, currently there is no way of knowing whether the user is viewing the ticker display, or whether the information being displayed by the ticker display has relevance to the user, and there is no way for advertisers and the like to capitalize on or change the information being displayed.
In view of the foregoing and other problems of the conventional systems and methods, it is an object of the present invention to provide a system for viewing information and data which is user-interactive.
Another object of the invention is to provide a system which integrates eye-tracking technology with ticker-like interfaces to significantly enhance the usability of the ticker interface.
Yet another object of the invention is to provide a system for generating relevance feedback which is helpful in improving the quality of Internet-based information systems.
A further object is to provide a system which determines whether the user is viewing the information being displayed, and, if so, determining a level of relevance to the user of the information being displayed by the ticker display.
In a first aspect of the present invention, a method for interactively displaying information, includes a display for displaying items having different views, a tracker for tracking a user's eye movements while observing a first view of information on the display, and a mechanism, based on an output, from the tracker, for determining whether a current view has relevance to the user.
In a second aspect of the present invention, a method for interactively displaying information, includes displaying items having different views, tracking a user's eye movements while observing a first view of information on the display, and, based on the tracking, determining whether a current view has relevance to the user.
With the unique and unobvious aspects and features of the present invention, the system can determine whether the user is viewing the ticker display, and, if so, whether the information being displayed by the ticker display has relevance to the user. Further, the present invention provides a hassle-free way of providing relevance feedback for the information being displayed and can automatically change the amount and type of information being displayed to a particular user. Thus, the system is adaptive to the user's interests and preferences, and thereby advertisers and the like can capitalize on or change the information being displayed to the particular user.
The foregoing and other objects, aspects and advantages will be better understood from the following detailed description of a preferred embodiment of the invention with reference to the drawings, in which:
FIG. 1 illustrates schematically an environment and configuration of a system 100 integrating a ticker display with an eye tracking apparatus according to the present invention;
FIG. 2 illustrates a block diagram of a CPU 2 of the system according to the present invention;
FIG. 3A illustrates a method of operation of the present invention;
FIG. 3B illustrates a method of tracking ticker users according to the present invention; and
FIG. 4 illustrates a storage medium for storing steps of the program for gaze-based tracking of items (e.g., ticker items) on the display.
Referring now to the drawings, and more particularly to FIGS. 1-3B, there is shown a preferred embodiment of the present invention.
FIG. 1 illustrates a system 100 for viewing information and data which is interactive, and more specifically a system which integrates eye-tracking technology with ticker-like interfaces to significantly enhance the usability of the ticker interface and to generate relevance feedback which is helpful in improving the quality of information systems such as Internet-based information systems.
The system 100 includes a commercially-available display 1, for receiving data inputs such as images and the like from a central processing unit (CPU) 2 or the like, and for providing a viewable output to a user. The display has a main display area 1 a (e.g., main text window), as well as an area 1 b for menu bars, tool bars, and the like, and an area 1 c for ticker-like displays to scroll across the screen.
The display 1, operatively coupled and interfaced with the CPU 2, may be implemented by any suitable computer display with sufficient ability to depict graphical images. For example, the display 1 may include a cathode ray tube (CRT), liquid crystal diode (LCD) screen, light emitting diode (LED) screen, or another suitable video apparatus.
A gaze-tracking apparatus 3 including a camera, for example, is provided either mounted in/on the display 1 or adjacent thereby and coupled to the display 1 and the CPU 2 to provide an input to the display 1.
Specifically, the gaze-tracking technology uses cameras, and infrared or other devices to sense, locate and follow the movement of a user's eyes.
A number of different gaze tracking approaches, suitable for the present invention, are surveyed in Young et al., “Methods & Designs: Survey of Eye Movement Recording Methods”, Behavior Research Methods & Instrumentation, 1975, Vol.7(5), pp. 397-429, which is incorporated herein in its entirety: Ordinarily skilled artisans, having the benefit of this disclosure, will also recognize a number of different devices suitable for use as the apparatus 3.
As a specific example of one gaze tracking approach for use in the present invention, reference is made to the following patents, mentioned above and incorporated herein in their entirety: (1) U.S. Pat. No. 4,536,670 to Hutchinson, issued Jun. 6, 1989 and entitled “Eye Movement Detector”; (2) U.S. Pat. No. 4,950,069 to Hutchinson, issued Aug. 21, 1990 and entitled “Eye Movement Detector With Improved Calibration and Speed”; and (3) U.S. Pat. No. 4,595,990 to Garwin et al., issued Jun. 17,1986 and entitled “Eye Controlled Information Transfer”. Also, although the invention's gaze tracking apparatus 2 may be a custom product, a commercially available product may be used instead, such as the EyeTrac Series 4000 product by Applied Science Labs, or the EyeGaze system by LC Technologies, Inc.
Advantageously, the invention is capable of accurate operation with inexpensive, relatively low-resolution gaze tracking apparatuses. For instance, significant benefits can be gained with gaze tracking accuracy ±3 degrees, which is a low error requirement for gaze tracking systems. With this level of permissible error, the gaze tracking apparatus 3 may comprise an inexpensive video camera, many of which are known and becoming increasingly popular for use in computer systems.
Thus, the gaze tracking apparatus monitors eye orientation of a user (operator) as the operator views a display 1 having items displayed thereon in a ticker-like fashion. According to the operator's eye orientation, the computer measures the point of the operator's gaze, called a “gaze position” and times the amount/duration of the operator's gaze, thereby providing one indication (e.g., indicia) of interest in the item being observed and one method of measuring interest in the item being displayed. The computer also calculates a region of video screen surrounding the operator's gaze position. This region, for example, may be a circle that is calculated to include the operator's “actual gaze point” (as opposed to measured gaze position) with a certain probability.
The output from the gaze-tracking apparatus 3 (e.g., representing the movement of a user's eyes) is provided to the CPU 2. The CPU 2 in turn includes processing algorithms to map the movement of the user's eyes in terms of position on the display screen to which the user is observing, the speed of the movements of the user's eyes, and some information about the eye itself such as shape, size, etc.
Commercial and research prototype eye-tracking systems locate the position of human eyes and follow their movement. Eye-tracking has been successfully used in graphic user interfaces (GUI) to assist users, such as handicapped users, in various tasks.
In FIG. 1, the gaze tracking apparatus (e.g., camera) 3 is shown separate from the display 1. However, the camera 2 may be mounted or preferably embedded in the display 1 to detect, through the aid of the CPU 2, the user's presence, and to find/detect the location of the user's eyes.
For example, such a camera system 3 could be the same system that is used for iris-based identification as described in U.S. Pat. No. 5,572,596, incorporated herein by reference.
Once the location of the user's eyes is found, the direction of the user's gaze is determined by means such as described in one of the above mentioned patents or disclosure, incorporated herein by reference.
The eye gaze is mapped to a location on a display 1 that has items of information being scrolled thereacross. Such mapping is well-known especially for one of ordinary skill in the art taking the present application as a whole.
FIG. 2 illustrates a block diagram of the CPU 2 and its constituent elements.
In an exemplary embodiment, the CPU 2 includes one or more application programs 201, an information source module 202 (e.g., a World-Wide Web (WWW) module in the exemplary embodiment), a gaze tracking module 203, an integration module 204, and a video module 205. It is noted that any type of information module may be employed, either additionally or alternatively to the exemplary WWW module 202.
The CPU 2 may be a custom-built machine, or one selected from any number of different products such as a known and commercially-available personal computer, computer workstation, mainframe computer, or another suitable digital data processing device. As an example, the CPU 2 may be an IBM THINKPAD® computer. Although such a CPU (computer) clearly includes a number of other components in addition those of FIG. 2, these components are omitted from FIG. 2 for ease of illustration and brevity.
The application programs 201 comprise various programs running on the CPU 2, and requiring operator input from time to time. This input may include text/images (e.g., entered via the gaze-tracking apparatus 3) as well as positional (if a cursor is employed with the system). Examples of application programs 201 include commercially available programs such as database programs, word processing, and the like.
The information sources module 202 includes a software module configured to receive and interpret signals from at least one information source. For example, as mentioned above, one information source may be the World-Wide Web. As a specific example, the module 202 may include a WWW driver that receives electrical signals representing inputs from the WWW 4.
The gaze tracking module 203 includes a software module configured to receive and interpret signals from the gaze tracking apparatus 3. As a specific example, the module 203 may include a program that receives electrical signals from the apparatus 3 and provides an x-y output representing an area or point (a number) where the operator is calculated to be gazing, called the “gaze position”.
The video module 204 comprises a product that generates video signals representing images of text, etc. These signals are compatible with the display 1, and cause the display 1 to show the corresponding images. The video module 204 may be provided by hardware, software, or a combination. As a more specific example, the video module 205 may be a video display card, such as a Super Video Graphics Applications (SVGA) card.
The integration module 205 serves to integrate various inputs with eye gaze input (from the gaze tracking apparatus 3 and gaze tracking module 203). The integration module 205 applies certain criteria to inputs from the apparatus 3 to determine what the user is gazing upon.
Although the software programming associated with the gaze tracking apparatus 3 may be included with the apparatus 3 itself, the particular example of FIG. 2 shows the associated software implemented in a gaze tracking module 203, as described below. The module 203 may be included solely in a CPU 2, in the apparatus 3 or in a combination of the two, depending upon the particular application.
In utilizing eye-tracking in GUI interfaces, the GUI component the user is paying attention to must be determined.
Whereas traditional GUI components, such as a text window or a menu bar, are static, ticker items follow a pre-determined pattern of motion. By tracking a user's eye movement and comparing such movement with the ticker's planned motion, a very high level of confidence can be established regarding whether the user is paying attention to a particular item. As an exemplary case, stock information will be examined below.
For example, suppose that a stock ticker is scrolling stock items from left to right on the bottom of the screen of display 1. If the eye-tracking system 3 in association with the CPU 2 has detected that the user's eyes moved from point (x1, y1) at time T to point (x2, y2) at speed P, and if a particular ticker item such as, for example, the stock of International Business Machines (IBM) Corporation, also moved from point (x1, y1) at time T to point (x2, y2) with the speed of P, and if the distance between (x1, y1) and (x2, y2) is sufficiently long (e.g., a few inches), it is highly likely that the user is paying close attention to the IBM stock. Such an eye-tracking system may be implemented through the use of a comparator (not illustrated) for comparing a user's eye position with a fixed position and a timer (not illustrated) which times the duration of a user scanning the display screen. The longer that the person scans a particular message or display would indicate that the user has a high interest in the content of the information.
It is noted that the motion of items in a ticker display can be designed to force an attentive user to have more complex eye movements than simple vertical or horizontal movement.
For example, a ticker in which items are printed in typewriter fashion will cause users to move their eyes both horizontally and vertically. A ticker in which items are displayed in different sectors of a circle will cause attentive users to have more dramatic eye movements. Generally, if the user's eye movements follow the planned movement of a particular ticker item, then the more complex the eye movements, the higher confidence and determination that the user is paying attention to the particular ticker item.
There are several benefits of using eye-tracking technology to determine whether a user is currently paying attention to a particular ticker item.
First, eye-tracking enables the ticker system to enhance its usability by automatically providing additional relevant (and more detailed) information of the subject being viewed. Thus, the items of information each may have different “views”. A “view” is a way to present information. As a rough example, time may be represented in various ways (or views) such as by Greenwich Mean Time (GMT) or Pacific Standard Time (PST). In a first view of “time”, only the local time may be provided (e.g., PST), whereas in a second view the GMT may be provided. Hence, different views represent different levels of detail of the information.
For example, to achieve this benefit, information related to the same topic may be organized into different views such as a cluster of pieces of different detail levels. Such organization may be performed in many ways and is believed to be well within the grasp of one of ordinary skill in the art within the purview of the present application.
Such information may be accessible through the World Wide Web (WWW) 4 or other storage facilities for storing related data such as a diskette, the CPU 2, a direct access storage device (DASD) storage (e.g., a conventional “hard drive” or a RAID array)! magnetic tape, electronic read-only memory (e.g., ROM, EPROM, or EEPROM), an optical storage device (e.g. CD-ROM, WORM, DVD, digital optical tape, etc.), paper “punch” cards, or any other suitable signal-bearing media including transmission media such as digital and analog and communication links and wireless.
For example, the top level view (or detail) could be the “highlight” information, which is directly displayed as an item by a ticker interface.
The second level could be the “abstract”, which contains information more than the highlight.
The third level could be “detail” information, which contains a detailed description of the topic.
Optionally, there can be a fourth level (or additional lower levels) of “related information”, which contains any other information that in some way is related to the topic.
For example and returning to the example of the IBM stock being displayed on a monitor in a ticker-like fashion, the “highlight” of the IBM stock may be just its current trading value. The “abstract” of the IBM stock may contain its day-high, day-low, trading volume, and other financial summary information. The “detail” of the IBM stock may contain its performance over the past year or other predetermined time frame (e.g., detailed financial data). The “related” information may contain important news about IBM, similar to that provided currently provided by PointCast and the MyYahoo web page.
When the eye-tracking system (e.g., through use of the comparator and timer or the like) detects that the user is paying attention to a particular ticker item, the ticker system can automatically display the corresponding abstract, using additional screen real estate such as a small pop up text window or the like. The abstract can stand still or move along with the highlight of the ticker item.
If the eye-tracking system further detects that the user is looking at the abstract for a sufficiently long period (e.g., relative to the size of the abstract), the ticker system may automatically display the corresponding detail, and even related information. Hence, “reading behavior” can be determined through eye tracking. Once again, such a feature may be implemented with a comparator and timer system in which the comparator determines that the user is looking at the abstract, and a time-out period is reached. Upon reaching the time-out period, then the subsequent level of information is displayed.
As mentioned above, the eye-tracking system may implement such detection of the user's observation through a comparator and a timer (e.g., a timer having a predetermined time period) which upon the expiration of the predetermined time period (e.g., 3 seconds or the like depending upon the amount of information being displayed) automatically and sequentially generates and displays the related abstract, detail, and related information, with each iteration of the count-down of the timer.
It is noted that the specific mechanisms (e.g., the mechanism for displaying the abstract, detail, etc.) can be implemented by simply activating a browser that goes to and displays the relevant Web pages.
FIG. 3A shows a sequence of method steps 300 to illustrate one example of the method aspect of the present invention. For ease of explanation, but without any limitation intended thereby, the example of FIG. 3A is described in the context of the hardware environment described above in FIGS. 1-2.
The process 300 is initiated in step 301. As an example, this may occur automatically through use of various known sensing mechanisms or the like, when the user requests a service, when the computer/CPU 2 boots-up, under control of one of the application programs 201, or when the operator manually activates a selection actuator (not illustrated) to indicate “start” to the inventive structure and method, or at another time.
In the illustrated example, when the routine 300 begins, the computer is booted up and the user is assumed to be observing ticker-like displays in step 301.
In response to step 302, the integration module 205 starts to monitor the operator's gaze position and the duration of the gaze position in step 303. The gaze position is a point where the gaze tracking apparatus 3 and gaze tracking module 203 calculate the operator's actual gaze point to be. This calculated point may include some error due to the limits of resolution of the gaze tracking apparatus 3, intrinsic difficulties in calculating gaze (e.g., accounting for head movement in corneal reflection systems, etc.), and other sources of error. These sources of error are collectively referred to as “system noise”, and may be understood by studying and measuring the operation of the system 100. For example, it may be determined in some systems that the error between gaze position and actual gaze point has a Gaussian distribution.
In step 304, if the duration of the operator's gaze is greater than or equal to a predetermined time “X”, then a second level of information is displayed in step 305. If the duration of the gaze is less than “X”, then the process reverts back to step 302 to simply continue displaying the ticker-like items. It is noted that activation by dwell time (e.g., based on predetermined time “X”), may be too slow or too fast for particular users. Thus, it is envisioned that the dwell time may be user-defined. Additionally or alternatively to the dwell time, the behavior of the user may be monitored to provide even greater reliability. Such behavior could be user-defined. Further, the eye position could be synchronized with the ticker context. Thus, the apparatus would “know” how much of the message was read, and which part the user spent more time reading.
Step 307 (e.g., signifying the last level of detail being displayed) is displayed if the duration of the gaze for the second level of information is greater than “X”. After the last level of detail is displayed, the process reverts back to step 302 or the process is completed when the CPU 2/display 1 are de-activated, as shown by step 308.
FIG. 3B illustrates a method of tracking ticker users according to the present invention.
Specifically, to read a static (e.g., non-moving) display, users characteristically move their eyes (e.g., saccade) mostly forward through the text approximately every 200 milliseconds, jumping approximately eight characters at a time (e.g., see Rayner, K. and Pollatsek, A., The Psychology of Reading. Hillsdale, N.J.: Erlbaum. (1989). Thus, normal reading ability suggests people read approximately 40 characters per second.
On a one-line scrolling ticker display, information (e.g., so-called “headlines”) flows right to left or top to bottom. Although eye-movement studies of users reading scrolling ticker displays are unknown, it is safe to assume that to read the headline, a user must look at it long enough to pick up all characters in the text. Given the standard reading data, then, for a five-word headline, the user would have to look at it for at least about one second to gather the characters of the text.
A method according to the present invention determines what headline a user is interested in proceeds as follows.
First, the user's eye position (e.g., an x and y location on the screen) is sampled approximately every 33 milliseconds (30 Hz). This position is used to determine what headline is being looked at (step 310).
More specifically, each headline is defined by a rectangle at a specific x and y location and with a specific width and height. Whereas the x (and/or y) location of the rectangle changes as the headline scrolls, its width and height remain constant.
Each time the user's eye position is sampled, the headline, if any, that the user is looking at is found by searching for the headline rectangle that contains the (x, y) position of the user's eyes (step 311). If one is found, this headline is considered to be the “current headline”. It is noted that the current headline may change between consecutive samples. However, if the headline does not change between consecutive samples, then the user is assumed to be looking at the headline. If “NO” in step 311, then the current headline, counter and threshold are set in step 315.
The period during which the user looks at a particular headline is calculated by incrementing a counter for each consecutive sample during which the current headline does not change (step 312).
If the period the user is looking at the headline crosses a threshold (e.g., determined by the number of characters or words in the headline, at a rate of roughly 35 characters per second), then the user is said to be interested in the headline (steps 312\3, 314). This provides positive feedback to the system.
FIG. 3B illustrates this method, and specifically a method for determining user relevance in ticker-displayed headlines based on eye fixation.
A similar method can be used to determine whether a user is not interested in a headline.
Specifically, each time the current headline changes before the period crosses the interest threshold, the user is said to be uninterested in the headline. This provides negative feedback to the system.
As shown in FIG. 4, in addition to the hardware and process environment described above, a different aspect of the invention includes a computer-implemented method for displaying ticker-like displays and measuring relevance feedback, as described above. As an example, this method may be implemented in the particular hardware environment discussed above.
Such a method may be implemented, for example, by operating the CPU 2 (FIG. 2), to execute a sequence of machine-readable instructions. These instructions may reside in various types of signal-bearing media.
Thus, this aspect of the present invention is directed to a programmed product, comprising signal-bearing media tangibly embodying a program of machine-readable instructions executable by a digital data processor incorporating the CPU 2 and hardware above, to perform a method to perform ticker-like displays.
This signal-bearing media may include, for example, a RAM (not shown) contained within the CPU 2, as represented by the fast-access storage for example. Alternatively, the instructions may be contained in another signal-bearing media, such as a magnetic data storage diskette 400 (FIG. 4), directly or indirectly accessible by the CPU 2.
Whether contained in the diskette 400, the computer 2, or elsewhere, the instructions may be stored on a variety of machine-readable data storage media, such as DASD storage (e.g., a conventional “hard drive” or a RAID array)! magnetic tape, electronic read-only memory (e.g., ROM, EPROM, or EEPROM), an optical storage device (e.g. CD-ROM, WORM, DVD, digital optical tape, etc.), paper “punch” cards, or other suitable signal-bearing media including transmission media such as digital and analog and communication links and wireless. In an illustrative embodiment of the invention, the machine-readable instructions may comprise software object code, compiled from a language such as “C”, etc.
Another approach to using eye movement information with the ticker is to modify what is displayed by the ticker itself. For example, the ticker item may be displayed in a bolder font, an underlined font, an italicized font, with greater resolution, or the like, if the user is tracking it. Specifically, the camera system would provide an input to the CPU 2 indicating that the user is paying particular attention to an information item. As a result, the item is of interest could be displayed differently from other items, as discussed above.
Moreover, to save screen real estate as well as free up ticker real estate for additional items to be output, the ticker item could be displayed in a narrower or smaller font (e.g., displayed with a different attribute), or could be displayed with less resolution than normal if not being tracked, if the camera/sensor determines that the user is not tracking it.
Additionally, the ticker speed could be controlled. For example, if the user is looking at the left of the screen and the ticker is about to disappear, the ticker speed could be slowed down, to allow the user to read the ticker. Further, if the user is looking to the right of the screen, the user is “waiting” for the ticker. Thus, the ticker speed could be increased. In this way, the system adapts to the user's reading speed.
A third possibility is that by paying attention to some ticker item, other related information (e.g., such as more views (levels of detail), or related news stories) is displayed by the ticker itself. Programming such a capability is believed to be well within the grasp of the ordinarily skilled artisan within the scope and purview of the present application.
With the above in mind, a second major advantage of combining eye-tracking with ticker displays becomes evident. That is, the system according to the present invention allows relevance feedback to be passively obtained.
With the massive amount of digital information, all Internet-based information systems face the challenge of providing the users with quality information that is relevant to their individual personal interests. Hence, most existing systems demand (or at least strongly request) that users provide an explicit interest profile or explicit vote on individual web pages. Such activities put significant burdens on users, who want merely to get the best information with the least trouble in the quickest possible manner.
By integrating eye-tracking with a ticker display, the system according to the present invention can automatically collect valuable feedback passively, without requiring the user to take any explicit action such as completing a survey form, undergoing a registration process, or the like.
Using the same techniques described previously for determining whether to display more relevant information to a user, the system generates relevance feedback based on whether the user is paying attention to certain ticker items. Accordingly, the system “learns” the user's particular interests, and the system “adaptively” provides information regarding such interests to the user.
A key advantage of this approach is that the system may have different levels of confidence in the user's interests in a certain topic because it provides different levels of details for any ticker item. Thus, the system is adaptive to the user's interests, and stores information broadly representing the user's interests in a database or the like.
For example, if a user always pays attention to the details of the IBM stock, the system will record in the user's profile a strong interest in IBM and will collect and provide more information related to IBM for the user. For example, such collection and searching may take place by the system going out on the Internet and searching for such information and bringing it to the user, if on-line, or storing it for future use and display. By the same token, as mentioned above, the system is adaptive and will learn and modify its searching and displaying parameters over time and based on the user. For example, if many users use a specific terminal/machine, the machine may store the profiles based on user passwords or the like.
Thus, if the same user does not pay attention to IBM news, this negative feedback can also be noted in the user's profile, and, eventually the user's ticker will display mainly IBM stock information and not IBM news.
It is noted that the above-described operations of tracking of a user's eye movements and comparing them with the item movements in a ticker display, dividing information into different levels of details, automatically providing more relevant information based on detected user attention, and obtaining useful relevance feedback, are but a single specific embodiment of integrating eye-tracking with ticker displays in general. There are many other ways to implement the present invention.
Thus, while the invention has been described in terms of a single preferred embodiment, those skilled in the art will recognize that the invention can be practiced with modification within the spirit and scope of the appended claims.
For example, an eye-tracking system can be installed on a television monitor for receiving broadcast signals. For channels such as CNBC, CSPN, etc, which display highlights and scores using tickers, this disclosure can be applied to create interactive TV features, such as automatically adjusting the TV display and programming based on what the user is watching.
Generally, tickers work by putting in a fixed set of information into a queue and starting the information moving across the screen one at a time from the queue. If the ticker is displaying paid-for advertising, the size of the fixed set is very important to the advertiser, since advertisers wish their advertisement to “roll” across the screen as often as possible so their is a high likelihood it will be noticed by a user.
For example, if the fixed set has 10 advertisement items, each advertisement appears every minute, whereas if the set has 10,000 advertisement items, each advertisement appears only once per day.
Advertisers could pay more to have more presentation time, but then many of the items in a large fixed set are duplicates. As new information is received, the ticker updates the candidate list fixed set by deleting older information and inserting the new information, as is known. Any relevance feedback during this step is beneficial. Ideally, the system deletes the uninteresting items, keeps the interesting items and adds new items to be presented. This allows for directed advertisement which saves the advertiser money, and makes the user happier since the user is presented with mainly interesting (or related) items. By using the gaze information of the user, this relevance feedback is non-obtrusive and automatic.
|Cited Patent||Filing date||Publication date||Applicant||Title|
|US4950069 *||Nov 4, 1988||Aug 21, 1990||University Of Virginia||Eye movement detector with improved calibration and speed|
|US5016282||Jul 12, 1989||May 14, 1991||Atr Communication Systems Research Laboratories||Eye tracking image pickup apparatus for separating noise from feature portions|
|US5507291||Apr 5, 1994||Apr 16, 1996||Stirbl; Robert C.||Method and an associated apparatus for remotely determining information as to person's emotional state|
|US5572596||Sep 2, 1994||Nov 5, 1996||David Sarnoff Research Center, Inc.||Automated, non-invasive iris recognition system and method|
|US5649061||May 11, 1995||Jul 15, 1997||The United States Of America As Represented By The Secretary Of The Army||Device and method for estimating a mental decision|
|US5762611||Nov 12, 1996||Jun 9, 1998||The United States Of America As Represented By The Secretary Of The Navy||Evaluation of a subject's interest in education, training and other materials using brain activity patterns|
|US5825355 *||Jan 27, 1993||Oct 20, 1998||Apple Computer, Inc.||Method and apparatus for providing a help based window system using multiple access methods|
|US5886683||Jun 25, 1996||Mar 23, 1999||Sun Microsystems, Inc.||Method and apparatus for eyetrack-driven information retrieval|
|US5898423 *||Jun 25, 1996||Apr 27, 1999||Sun Microsystems, Inc.||Method and apparatus for eyetrack-driven captioning|
|US5920477 *||Jun 6, 1995||Jul 6, 1999||Hoffberg; Steven M.||Human factored interface incorporating adaptive pattern recognition based controller apparatus|
|US5959621 *||Dec 6, 1996||Sep 28, 1999||Microsoft Corporation||System and method for displaying data items in a ticker display pane on a client computer|
|US5987415||Jun 30, 1998||Nov 16, 1999||Microsoft Corporation||Modeling a user's emotion and personality in a computer user interface|
|US6067565||Jan 15, 1998||May 23, 2000||Microsoft Corporation||Technique for prefetching a web page of potential future interest in lieu of continuing a current information download|
|US6134644 *||Jan 14, 1998||Oct 17, 2000||Fujitsu Limited||Method and apparatus for reproducing operation guidance information, and method and apparatus for reproducing multi-media information|
|US6182098 *||Jul 22, 1998||Jan 30, 2001||International Business Machines Corporation||Next/current/last ticker graphical presentation method|
|US6185534||Mar 23, 1998||Feb 6, 2001||Microsoft Corporation||Modeling emotion and personality in a computer user interface|
|US6212502||Jun 30, 1998||Apr 3, 2001||Microsoft Corporation||Modeling and projecting emotion and personality from a computer user interface|
|US6351273 *||Apr 30, 1997||Feb 26, 2002||Jerome H. Lemelson||System and methods for controlling automatic scrolling of information on a display or screen|
|1||Black et al., "Recognizing Facial Expressions in Image Sequences using Local Parameterized Models of Image Motion", pp. 1-35, Mar. 1995.|
|2||Ebisawa, et al, "Examination of Eye-Gaze Detection Technique Using Two Light Sources and the Image Difference Method", SICE '94, Jul. 26-28, 1994.|
|3||Ebisawa, Y., "Improved Video-Based Eye-Gaze Detection Method", IMTC '94 May 10-12, 1994.|
|4||Erik D. Reichle, Alexander Pollatsek, Donald L. Fisher, and Keith Rayner, University of Massachusetts at Amherst, "Toward a Model of Eye Movement Control in Reading", Psychological Review 1998; vol. 105, No. 1, pp. 125-157.|
|5||Eriksson, M., "Eye-Tracking for Detection of Driver Fatigue", IEEE Conference on Intelligent Transportation Systems, Nov. 9-12, pp. 314-319.|
|6||Funada, et al., "On an Image Processing of Eye Blinking to Monitor Awakening Levels of Human Beings", IEEE Conference, pp. 966-967., 1996.|
|7||H. Rex Hartson and Deborah Hix, "Advances in Human-Computer Interaction", vol. 4, Virginia Polytechnic Institute and State University, ABLEX Publishing Corporation, Norwood, New Jersey, pp. 151-190, May 1993.|
|8||Johnmarshall Reeve and Glen Nix, "Expressing Intrinsic Motivation Through Acts of Exploration and Facial Displays of Interest", Motivation and Emotion, vol. 21, No. 3, 1997, pp. 237-250, 8 Pages Total.|
|9||Johnmarshall Reeve, "The Face of Interest", Motivation and Emotion, vol. 17, No. 4, 1993, pp. 353-375 12 Pages Total.|
|10||Kamitani, et al., "Analysis of perplex situations in word processor work using facial image sequence", SPIE vol. 3016, pp. 324-334., 1997.|
|11||Kumakura, S., "Apparatus for estimating the drowsiness level of a vehicle driver", Jul. 28, 1998, pp. 1-2.|
|12||Lien, et al, "Automated Facial Expression Recognition Based on FACS Action Units", Apr. 14-16, 1998, IEEE, Published in the Proceedings of FG '98, Nara, Japan.|
|13||Lien, et al, "Automatically Recognizing Facial Expressions in the Spatio-Temporal Domain", Oct. 19-21, 1997, Workshop on Perceptual User Interfaces, pp. 94-97, Banff, Alberta, Canada.|
|14||Lien, et al., "Subtly Different Facial Expression Recognition And Expression Intensity Estimation", Jun. 1998, IEEE, Published in the Proceedings of CVPR'98, Santa Barbara, CA.|
|15||Lisetti, et al, "An Environment to Acknowledge the Interface between Affect and Cognition", pp. 78-86.|
|16||Morimoto, et al., "Pupil Detection and Tracking Using Multiple Light Sources".|
|17||Morimoto, et al., "Recognition of Head Gestures Using Hidden Markov Models".|
|18||Ohtani, et al., "Eye-Gaze Detection Based on the Pupil Detection Technique Using Two Light Sources and the Image Difference Method", Sep. 20-23, 1995, pp. 1623-1624.|
|19||Pantic, et al., "Automated Facial Expression analysis", pp. 194-200.|
|20||Pantic, et al., "Automation of Non-Verbal Communication of Facial Expressions", pp. 86-93.|
|21||Paul P. Maglio, Rob Barrett, Christopher S. Campbell, Ted Selker, IBM Almaden Research Center, San Jose, CA., "Suitor: An Attentive Information System", IUI2000: The International Conference on Intelligent User Interfaces, pp. 1-8.|
|22||Robert J.K. Jacob, Human-Computer Interaction Lab, Naval Research Laboratory, Washington, D.C., "What You Look at is What You Get: Eye Movement-Based Interaction Techniques", CHI '90 Proceedings, Apr. 1990, pp. 11-18.|
|23||Tomono, et al., "A TV Camera System which Extracts Feature Points for Non-Contact Eye Movement Detection", SPIE vol. 1194 Optics, Illumination, and Image Sensing for Machine Vision IV (1989), pp. 2-12.|
|24||Y. Ebisawa, "Unconstrained pupil detection technique using two light sources and the image difference method", Visualization and Intelligent Design in Engineering, pp. 79-89, 1995.|
|Citing Patent||Filing date||Publication date||Applicant||Title|
|US7113170 *||Nov 8, 2002||Sep 26, 2006||Swisscom Mobile Ag||Method and terminal for entering instructions|
|US7120880 *||Feb 25, 1999||Oct 10, 2006||International Business Machines Corporation||Method and system for real-time determination of a subject's interest level to media content|
|US7167562 *||Jul 6, 2001||Jan 23, 2007||Dhva, Inc.||Security method using information transmission by optical means, and an optical disk for implementing the method|
|US7281199 *||Apr 27, 2000||Oct 9, 2007||Verizon Corporate Services Group Inc.||Methods and systems for selection of multimedia presentations|
|US7428744 *||Jun 18, 1999||Sep 23, 2008||Swisscom Mobile Ag||Method and device for detecting data concerning the viewing of video information and the relaying of this information to a central data processing installation|
|US7444383||Jun 30, 2003||Oct 28, 2008||Microsoft Corporation||Bounded-deferral policies for guiding the timing of alerting, interaction and communications using local sensory information|
|US7532197||Jun 22, 2004||May 12, 2009||Lenovo (Singapore) Pte Ltd.||Method and system for automated monitoring of a display|
|US7573439 *||Mar 10, 2005||Aug 11, 2009||General Electric Company||System and method for significant image selection using visual tracking|
|US7702624||Apr 19, 2005||Apr 20, 2010||Exbiblio, B.V.||Processing techniques for visual capture data from a rendered document|
|US7706611||Aug 23, 2005||Apr 27, 2010||Exbiblio B.V.||Method and system for character recognition|
|US7707039||Dec 3, 2004||Apr 27, 2010||Exbiblio B.V.||Automatic modification of web pages|
|US7725832||Apr 3, 2006||May 25, 2010||Microsoft Corporation||System and process for providing dynamic communication access and information awareness in an interactive peripheral display|
|US7742953||Jun 22, 2010||Exbiblio B.V.||Adding information or functionality to a rendered document via association with an electronic counterpart|
|US7743340 *||Jun 30, 2003||Jun 22, 2010||Microsoft Corporation||Positioning and rendering notification heralds based on user's focus of attention and activity|
|US7762665||Jul 27, 2010||Queen's University At Kingston||Method and apparatus for communication between humans and devices|
|US7769632||Aug 3, 2010||Promovu, Inc.||System for selectively communicating promotional information to a person|
|US7812860||Oct 12, 2010||Exbiblio B.V.||Handheld device for capturing text from both a document printed on paper and a document displayed on a dynamic display device|
|US7818215||May 17, 2005||Oct 19, 2010||Exbiblio, B.V.||Processing techniques for text capture from a rendered document|
|US7831912||Nov 9, 2010||Exbiblio B. V.||Publishing techniques for adding value to a rendered document|
|US7844666||Nov 30, 2010||Microsoft Corporation||Controls and displays for acquiring preferences, inspecting behavior, and guiding the learning and decision policies of an adaptive communications prioritization and routing system|
|US7975015||Jul 5, 2011||Microsoft Corporation||Notification platform architecture|
|US7990556||Feb 28, 2006||Aug 2, 2011||Google Inc.||Association of a portable scanner with input/output and storage devices|
|US8005720||Aug 23, 2011||Google Inc.||Applying scanned information to identify content|
|US8019648||Sep 13, 2011||Google Inc.||Search engines and systems with handheld document data capture devices|
|US8019834||Sep 13, 2011||Microsoft Corporation||Harnessing information about the timing of a user's client-server interactions to enhance messaging and collaboration services|
|US8024415||Mar 16, 2001||Sep 20, 2011||Microsoft Corporation||Priorities generation and management|
|US8074161||Jun 6, 2007||Dec 6, 2011||Verizon Patent And Licensing Inc.||Methods and systems for selection of multimedia presentations|
|US8081849||Feb 6, 2007||Dec 20, 2011||Google Inc.||Portable scanning and memory device|
|US8086672||Jun 30, 2004||Dec 27, 2011||Microsoft Corporation||When-free messaging|
|US8090706 *||Dec 21, 2007||Jan 3, 2012||Google, Inc.||Rendering advertisements with documents having one or more topics using user topic interest information|
|US8156186||Nov 11, 2005||Apr 10, 2012||Scenera Technologies, Llc||Method and system for organizing electronic messages using eye-gaze technology|
|US8179563||Sep 29, 2010||May 15, 2012||Google Inc.||Portable scanning device|
|US8185845||May 24, 2005||May 22, 2012||Tobii Technology Ab||Arrangement, method and computer program for controlling a computer apparatus based on eye-tracking|
|US8209224||Oct 29, 2009||Jun 26, 2012||The Nielsen Company (Us), Llc||Intracluster content management using neuro-response priming data|
|US8214387||Jul 3, 2012||Google Inc.||Document enhancement system and method|
|US8219438||Jul 10, 2012||Videomining Corporation||Method and system for measuring shopper response to products based on behavior and facial expression|
|US8232962 *||Jul 31, 2012||Trading Technologies International, Inc.||System and method for display management based on user attention inputs|
|US8249931||Aug 21, 2012||Promovu, Inc.||System for selectively communicating promotional information to a person|
|US8255827||Jan 26, 2009||Aug 28, 2012||Microsoft Corporation||Dynamic feature presentation based on vision detection|
|US8261094||Aug 19, 2010||Sep 4, 2012||Google Inc.||Secure data gathering from rendered documents|
|US8270814||Sep 18, 2012||The Nielsen Company (Us), Llc||Methods and apparatus for providing video with embedded media|
|US8292433||Sep 19, 2005||Oct 23, 2012||Queen's University At Kingston||Method and apparatus for communication between humans and devices|
|US8296285 *||Oct 23, 2012||Google Inc.||Rendering advertisements with documents having one or more topics using user topic interest information|
|US8322856||Jun 27, 2012||Dec 4, 2012||Queen's University At Kingston||Method and apparatus for communication between humans and devices|
|US8327395||Oct 2, 2008||Dec 4, 2012||The Nielsen Company (Us), Llc||System providing actionable insights based on physiological responses from viewers of media|
|US8332883||Oct 2, 2008||Dec 11, 2012||The Nielsen Company (Us), Llc||Providing actionable insights based on physiological responses from viewers of media|
|US8335715||Dec 18, 2012||The Nielsen Company (Us), Llc.||Advertisement exchange using neuro-response data|
|US8335716||Nov 19, 2009||Dec 18, 2012||The Nielsen Company (Us), Llc.||Multimedia advertisement exchange|
|US8346620||Jan 1, 2013||Google Inc.||Automatic modification of web pages|
|US8386312||Feb 26, 2013||The Nielsen Company (Us), Llc||Neuro-informatics repository system|
|US8386313||Feb 26, 2013||The Nielsen Company (Us), Llc||Stimulus placement system using subject neuro-response measurements|
|US8392250||Mar 5, 2013||The Nielsen Company (Us), Llc||Neuro-response evaluated stimulus in virtual reality environments|
|US8392251||Aug 9, 2010||Mar 5, 2013||The Nielsen Company (Us), Llc||Location aware presentation of stimulus material|
|US8392253||May 16, 2008||Mar 5, 2013||The Nielsen Company (Us), Llc||Neuro-physiology and neuro-behavioral based stimulus targeting system|
|US8392254||Mar 5, 2013||The Nielsen Company (Us), Llc||Consumer experience assessment system|
|US8392255||Mar 5, 2013||The Nielsen Company (Us), Llc||Content based selection and meta tagging of advertisement breaks|
|US8396744||Mar 12, 2013||The Nielsen Company (Us), Llc||Effective virtual reality environments for presentation of marketing materials|
|US8407620||Mar 26, 2013||Jonathan J. Cadiz||System and process for providing dynamic communication access and information awareness in an interactive peripheral display|
|US8412787||Apr 2, 2013||Scenera Technologies, Llc||Method and system for organizing electronic messages using eye-gaze technology|
|US8418055||Apr 9, 2013||Google Inc.||Identifying a document by performing spectral analysis on the contents of the document|
|US8442331||Aug 18, 2009||May 14, 2013||Google Inc.||Capturing text from rendered documents using supplemental information|
|US8447066||Mar 12, 2010||May 21, 2013||Google Inc.||Performing actions based on capturing information from rendered documents, such as documents under copyright|
|US8458032||Jul 13, 2012||Jun 4, 2013||Promovu, Inc.||System for selectively communicating promotional information to a person|
|US8464288||Jun 11, 2013||The Nielsen Company (Us), Llc||Methods and apparatus for providing personalized media in video|
|US8473345||Mar 26, 2008||Jun 25, 2013||The Nielsen Company (Us), Llc||Protocol generator and presenter device for analysis of marketing and entertainment effectiveness|
|US8484081||Mar 26, 2008||Jul 9, 2013||The Nielsen Company (Us), Llc||Analysis of marketing and entertainment effectiveness using central nervous system, autonomic nervous system, and effector data|
|US8489624||Jan 29, 2010||Jul 16, 2013||Google, Inc.||Processing techniques for text capture from a rendered document|
|US8494610||Sep 19, 2008||Jul 23, 2013||The Nielsen Company (Us), Llc||Analysis of marketing and entertainment effectiveness using magnetoencephalography|
|US8494905||Jun 6, 2008||Jul 23, 2013||The Nielsen Company (Us), Llc||Audience response analysis using simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI)|
|US8505090||Feb 20, 2012||Aug 6, 2013||Google Inc.||Archive of text captures from rendered documents|
|US8510166 *||May 11, 2011||Aug 13, 2013||Google Inc.||Gaze tracking system|
|US8515816||Apr 1, 2005||Aug 20, 2013||Google Inc.||Aggregate analysis of text captures performed by multiple users from rendered documents|
|US8533042||Jul 30, 2008||Sep 10, 2013||The Nielsen Company (Us), Llc||Neuro-response stimulus and stimulus attribute resonance estimator|
|US8538816 *||Jan 31, 2005||Sep 17, 2013||International Business Machines Corporation||Method of rewarding the viewing of advertisements based on eye-gaze patterns|
|US8539359 *||Feb 11, 2009||Sep 17, 2013||Jeffrey A. Rapaport||Social network driven indexing system for instantly clustering people with concurrent focus on same topic into on-topic chat rooms and/or for generating on-topic search results tailored to user preferences regarding topic|
|US8547330||May 23, 2012||Oct 1, 2013||Trading Technologies International, Inc.||System and method for display management based on user attention inputs|
|US8548852||Aug 8, 2012||Oct 1, 2013||The Nielsen Company (Us), Llc||Effective virtual reality environments for presentation of marketing materials|
|US8560429||Jan 10, 2012||Oct 15, 2013||Trading Technologies International, Inc.||System and method for assisted awareness|
|US8566413||Oct 27, 2008||Oct 22, 2013||Microsoft Corporation||Bounded-deferral policies for guiding the timing of alerting, interaction and communications using local sensory information|
|US8600196||Jul 6, 2010||Dec 3, 2013||Google Inc.||Optical scanners, such as hand-held optical scanners|
|US8620083||Oct 5, 2011||Dec 31, 2013||Google Inc.||Method and system for character recognition|
|US8635105||Aug 27, 2008||Jan 21, 2014||The Nielsen Company (Us), Llc||Consumer experience portrayal effectiveness assessment system|
|US8638363||Feb 18, 2010||Jan 28, 2014||Google Inc.||Automatically capturing information, such as capturing information using a document-aware device|
|US8655428||May 12, 2010||Feb 18, 2014||The Nielsen Company (Us), Llc||Neuro-response data synchronization|
|US8655437||Aug 21, 2009||Feb 18, 2014||The Nielsen Company (Us), Llc||Analysis of the mirror neuron system for evaluation of stimulus|
|US8672482||Apr 19, 2013||Mar 18, 2014||Queen's University At Kingston||Method and apparatus for communication between humans and devices|
|US8701027||Jun 15, 2001||Apr 15, 2014||Microsoft Corporation||Scope user interface for displaying the priorities and properties of multiple informational items|
|US8713418||Apr 12, 2005||Apr 29, 2014||Google Inc.||Adding value to a rendered document|
|US8721341 *||Mar 2, 2005||May 13, 2014||Optimetrics, Inc.||Simulated training environments based upon foveated object events|
|US8762202||Apr 11, 2012||Jun 24, 2014||The Nielson Company (Us), Llc||Intracluster content management using neuro-response priming data|
|US8775252||May 4, 2007||Jul 8, 2014||National Ict Australia Limited||Electronic media system|
|US8781228||Sep 13, 2012||Jul 15, 2014||Google Inc.||Triggering actions in response to optically or acoustically capturing keywords from a rendered document|
|US8799099||Sep 13, 2012||Aug 5, 2014||Google Inc.||Processing techniques for text capture from a rendered document|
|US8826168 *||Mar 15, 2010||Sep 2, 2014||The Marlin Company||Secure electronic media distribution and presentation system|
|US8831365||Mar 11, 2013||Sep 9, 2014||Google Inc.||Capturing text from rendered documents using supplement information|
|US8843346||May 13, 2011||Sep 23, 2014||Amazon Technologies, Inc.||Using spatial information with device interaction|
|US8854302 *||Aug 16, 2013||Oct 7, 2014||Trading Technologies International, Inc.||System and method for display management based on user attention inputs|
|US8860787||May 11, 2011||Oct 14, 2014||Google Inc.||Method and apparatus for telepresence sharing|
|US8862764||Mar 16, 2012||Oct 14, 2014||Google Inc.||Method and Apparatus for providing Media Information to Mobile Devices|
|US8874504||Mar 22, 2010||Oct 28, 2014||Google Inc.||Processing techniques for visual capture data from a rendered document|
|US8885877||May 20, 2011||Nov 11, 2014||Eyefluence, Inc.||Systems and methods for identifying gaze tracking scene reference locations|
|US8892495||Jan 8, 2013||Nov 18, 2014||Blanding Hovenweep, Llc||Adaptive pattern recognition based controller apparatus and method and human-interface therefore|
|US8911087||May 20, 2011||Dec 16, 2014||Eyefluence, Inc.||Systems and methods for measuring reactions of head, eyes, eyelids and pupils|
|US8929589||Nov 7, 2011||Jan 6, 2015||Eyefluence, Inc.||Systems and methods for high-resolution gaze tracking|
|US8930478||Mar 28, 2013||Jan 6, 2015||Scenera Technologies, Llc||Method and system for organizing electronic messages using eye-gaze technology|
|US8943425 *||Oct 30, 2007||Jan 27, 2015||Google Technology Holdings LLC||Method and apparatus for context-aware delivery of informational content on ambient displays|
|US8953886||Aug 8, 2013||Feb 10, 2015||Google Inc.||Method and system for character recognition|
|US8955010||Jun 10, 2013||Feb 10, 2015||The Nielsen Company (Us), Llc||Methods and apparatus for providing personalized media in video|
|US8957847 *||Dec 28, 2010||Feb 17, 2015||Amazon Technologies, Inc.||Low distraction interfaces|
|US8977110||Aug 9, 2012||Mar 10, 2015||The Nielsen Company (Us), Llc||Methods and apparatus for providing video with embedded media|
|US8989835||Dec 27, 2012||Mar 24, 2015||The Nielsen Company (Us), Llc||Systems and methods to gather and analyze electroencephalographic data|
|US8990235||Mar 12, 2010||Mar 24, 2015||Google Inc.||Automatically providing content associated with captured information, such as information captured in real-time|
|US9008447||Apr 1, 2005||Apr 14, 2015||Google Inc.||Method and system for character recognition|
|US9021515||Oct 24, 2012||Apr 28, 2015||The Nielsen Company (Us), Llc||Systems and methods to determine media effectiveness|
|US9030699||Aug 13, 2013||May 12, 2015||Google Inc.||Association of a portable scanner with input/output and storage devices|
|US9035878 *||Feb 29, 2012||May 19, 2015||Google Inc.||Input system|
|US9047256||Dec 30, 2009||Jun 2, 2015||Iheartmedia Management Services, Inc.||System and method for monitoring audience in response to signage|
|US9053462 *||Jan 22, 2007||Jun 9, 2015||Microsoft Technology Licensing, Llc||User interface for a system and process for providing dynamic communication access and information awareness in an interactive peripheral display|
|US9060671||Dec 27, 2012||Jun 23, 2015||The Nielsen Company (Us), Llc||Systems and methods to gather and analyze electroencephalographic data|
|US9075779||Apr 22, 2013||Jul 7, 2015||Google Inc.||Performing actions based on capturing information from rendered documents, such as documents under copyright|
|US9081799||Dec 6, 2010||Jul 14, 2015||Google Inc.||Using gestalt information to identify locations in printed information|
|US9106958||Feb 27, 2012||Aug 11, 2015||Affectiva, Inc.||Video recommendation based on affect|
|US9116890||Jun 11, 2014||Aug 25, 2015||Google Inc.||Triggering actions in response to optically or acoustically capturing keywords from a rendered document|
|US9143638||Apr 29, 2013||Sep 22, 2015||Google Inc.||Data capture from rendered documents using handheld device|
|US9152221 *||Sep 28, 2012||Oct 6, 2015||Sri International||Method, apparatus, and system for modeling passive and active user interactions with a computer system|
|US9152222||Sep 28, 2012||Oct 6, 2015||Sri International||Method, apparatus, and system for facilitating cross-application searching and retrieval of content using a contextual user model|
|US9158370||Sep 28, 2012||Oct 13, 2015||Sri International||Method, apparatus, and system for modeling interactions of a group of users with a computing system|
|US9204836||Oct 26, 2013||Dec 8, 2015||Affectiva, Inc.||Sporadic collection of mobile affect data|
|US9215978||Jan 30, 2015||Dec 22, 2015||The Nielsen Company (Us), Llc||Systems and methods to gather and analyze electroencephalographic data|
|US9223854 *||Dec 21, 2009||Dec 29, 2015||Hewlett-Packard Development Company, L.P.||Document relevance determining method and computer program|
|US9235264||Dec 18, 2014||Jan 12, 2016||Scenera Technologies, Llc||Method and system for organizing electronic messages using eye-gaze technology|
|US9235576||Nov 28, 2011||Jan 12, 2016||Verizon Patent And Licensing Inc.||Methods and systems for selection of multimedia presentations|
|US9247903||Feb 6, 2012||Feb 2, 2016||Affectiva, Inc.||Using affect within a gaming context|
|US9261958 *||Jun 28, 2010||Feb 16, 2016||Samsung Electronics Co., Ltd.||Apparatus and method for navigation in digital object using gaze information of user|
|US9265458||Dec 4, 2012||Feb 23, 2016||Sync-Think, Inc.||Application of smooth pursuit cognitive testing paradigms to clinical drug development|
|US9268852||Sep 13, 2012||Feb 23, 2016||Google Inc.||Search engines and systems with handheld document data capture devices|
|US9274598 *||Apr 29, 2004||Mar 1, 2016||International Business Machines Corporation||System and method for selecting and activating a target object using a combination of eye gaze and key presses|
|US9275051||Nov 7, 2012||Mar 1, 2016||Google Inc.||Automatic modification of web pages|
|US9292858||Feb 27, 2012||Mar 22, 2016||The Nielsen Company (Us), Llc||Data collection system for aggregating biologically based measures in asynchronous geographically distributed public environments|
|US9320450||Mar 14, 2013||Apr 26, 2016||The Nielsen Company (Us), Llc||Methods and apparatus to gather and analyze electroencephalographic data|
|US9323784||Dec 9, 2010||Apr 26, 2016||Google Inc.||Image search using text-based elements within the contents of images|
|US9336535||Feb 11, 2014||May 10, 2016||The Nielsen Company (Us), Llc||Neuro-response data synchronization|
|US20020031227 *||Jul 6, 2001||Mar 14, 2002||Maurice Milgram||Security method using information transmission by optical means, and an optical disk for implementing the method|
|US20020054117 *||Jun 15, 2001||May 9, 2002||Van Dantzich Maarten R.||Scope user interface for displaying the priorities and properties of multiple informational items|
|US20020087649 *||Jun 14, 2001||Jul 4, 2002||Horvitz Eric J.||Bounded-deferral policies for reducing the disruptiveness of notifications|
|US20030046421 *||Dec 12, 2001||Mar 6, 2003||Horvitz Eric J.||Controls and displays for acquiring preferences, inspecting behavior, and guiding the learning and decision policies of an adaptive communications prioritization and routing system|
|US20030076300 *||Nov 8, 2002||Apr 24, 2003||Eric Lauper||Method and terminal for entering instructions|
|US20040030753 *||Jun 30, 2003||Feb 12, 2004||Horvitz Eric J.||Bounded-deferral policies for guiding the timing of alerting, interaction and communications using local sensory information|
|US20040098462 *||Jun 30, 2003||May 20, 2004||Horvitz Eric J.||Positioning and rendering notification heralds based on user's focus of attention and activity|
|US20040143636 *||Mar 16, 2001||Jul 22, 2004||Horvitz Eric J||Priorities generation and management|
|US20040183749 *||Mar 21, 2003||Sep 23, 2004||Roel Vertegaal||Method and apparatus for communication between humans and devices|
|US20040254998 *||Jun 30, 2004||Dec 16, 2004||Microsoft Corporation||When-free messaging|
|US20050047629 *||Aug 25, 2003||Mar 3, 2005||International Business Machines Corporation||System and method for selectively expanding or contracting a portion of a display using eye-gaze tracking|
|US20050108092 *||Jan 31, 2005||May 19, 2005||International Business Machines Corporation||A Method of Rewarding the Viewing of Advertisements Based on Eye-Gaze Patterns|
|US20050195165 *||Mar 2, 2005||Sep 8, 2005||Mitchell Brian T.||Simulated training environments based upon foveated object events|
|US20050243054 *||Apr 29, 2004||Nov 3, 2005||International Business Machines Corporation||System and method for selecting and activating a target object using a combination of eye gaze and key presses|
|US20060007396 *||Jun 22, 2004||Jan 12, 2006||International Business Machines Corporation||Method and system for automated monitoring of a display|
|US20060037038 *||Jun 21, 2004||Feb 16, 2006||Trading Technologies International, Inc.||System and method for display management based on user attention inputs|
|US20060039272 *||Aug 23, 2004||Feb 23, 2006||Divaydeep Sikri||Multi-band wideband transmission methods and apparatus having improved user capacity|
|US20060066567 *||Sep 29, 2004||Mar 30, 2006||Scharenbroch Gregory K||System and method of controlling scrolling text display|
|US20060093998 *||Sep 19, 2005||May 4, 2006||Roel Vertegaal||Method and apparatus for communication between humans and devices|
|US20060109238 *||Mar 10, 2005||May 25, 2006||General Electric Company||System and method for significant image selection using visual tracking|
|US20060140420 *||Dec 23, 2004||Jun 29, 2006||Akihiro Machida||Eye-based control of directed sound generation|
|US20060179415 *||Apr 3, 2006||Aug 10, 2006||Microsoft Corporation||User interface for a system and process for providing dynamic communication access and information awareness in an interactive peripheral display|
|US20060265651 *||May 2, 2006||Nov 23, 2006||Trading Technologies International, Inc.||System and method for display management based on user attention inputs|
|US20060290663 *||Aug 29, 2006||Dec 28, 2006||Mitchell Brian T||Simulated training environments based upon fixated objects in specified regions|
|US20070112916 *||Nov 11, 2005||May 17, 2007||Singh Mona P||Method and system for organizing electronic messages using eye-gaze technology|
|US20070129817 *||Jan 22, 2007||Jun 7, 2007||Microsoft Corporation||User Interface for a System and Process for Providing Dynamic Communication Access and Information Awareness in an Interactive Peripheral Display|
|US20070164990 *||May 24, 2005||Jul 19, 2007||Christoffer Bjorklund||Arrangement, method and computer program for controlling a computer apparatus based on eye-tracking|
|US20070214228 *||May 16, 2007||Sep 13, 2007||Microsoft Corporation||Notification platform architecture|
|US20080097833 *||Dec 21, 2007||Apr 24, 2008||Krishna Bharat||Rendering advertisements with documents having one or more topics using user topic interest information|
|US20080215975 *||Apr 23, 2007||Sep 4, 2008||Phil Harrison||Virtual world user opinion & response monitoring|
|US20080256454 *||Apr 13, 2007||Oct 16, 2008||Sap Ag||Selection of list item using invariant focus location|
|US20090024049 *||Mar 26, 2008||Jan 22, 2009||Neurofocus, Inc.||Cross-modality synthesis of central nervous system, autonomic nervous system, and effector data|
|US20090024449 *||May 16, 2008||Jan 22, 2009||Neurofocus Inc.||Habituation analyzer device utilizing central nervous system, autonomic nervous system and effector system measurements|
|US20090094628 *||Oct 2, 2008||Apr 9, 2009||Lee Hans C||System Providing Actionable Insights Based on Physiological Responses From Viewers of Media|
|US20090112656 *||Dec 11, 2007||Apr 30, 2009||Searete Llc, A Limited Liability Corporation Of The State Of Delaware||Returning a personalized advertisement|
|US20090112693 *||Nov 30, 2007||Apr 30, 2009||Jung Edward K Y||Providing personalized advertising|
|US20090112694 *||Nov 30, 2007||Apr 30, 2009||Searete Llc, A Limited Liability Corporation Of The State Of Delaware||Targeted-advertising based on a sensed physiological response by a person to a general advertisement|
|US20090112696 *||Jan 3, 2008||Apr 30, 2009||Jung Edward K Y||Method of space-available advertising in a mobile device|
|US20090112713 *||Jan 3, 2008||Apr 30, 2009||Searete Llc, A Limited Liability Corporation Of The State Of Delaware||Opportunity advertising in a mobile device|
|US20090113297 *||Oct 25, 2007||Apr 30, 2009||Searete Llc, A Limited Liability Corporation Of The State Of Delaware||Requesting a second content based on a user's reaction to a first content|
|US20090113298 *||Oct 24, 2007||Apr 30, 2009||Searete Llc, A Limited Liability Corporation Of The State Of Delaware||Method of selecting a second content based on a user's reaction to a first content|
|US20090113346 *||Oct 30, 2007||Apr 30, 2009||Motorola, Inc.||Method and apparatus for context-aware delivery of informational content on ambient displays|
|US20090131764 *||Oct 31, 2008||May 21, 2009||Lee Hans C||Systems and Methods Providing En Mass Collection and Centralized Processing of Physiological Responses from Viewers|
|US20090177528 *||May 4, 2007||Jul 9, 2009||National Ict Australia Limited||Electronic media system|
|US20090299814 *||May 31, 2008||Dec 3, 2009||International Business Machines Corporation||Assessing personality and mood characteristics of a customer to enhance customer satisfaction and improve chances of a sale|
|US20090299934 *||Jun 1, 2009||Dec 3, 2009||Microsoft Corporation||Harnessing information about the timing of a user's client-server interactions to enhance messaging and collaboration services|
|US20100145215 *||Aug 20, 2009||Jun 10, 2010||Neurofocus, Inc.||Brain pattern analyzer using neuro-response data|
|US20100146461 *||Aug 5, 2009||Jun 10, 2010||Samsung Electronics Co., Ltd.||Electronic apparatus and displaying method thereof|
|US20100175017 *||Mar 15, 2010||Jul 8, 2010||Kenna Iii Frank||Secure Electronic Media Distribution And Presentation System|
|US20100191727 *||Jan 26, 2009||Jul 29, 2010||Microsoft Corporation||Dynamic feature presentation based on vision detection|
|US20100199190 *||Aug 5, 2010||Microsoft Corporation||System and process for providing dynamic communication access and information awareness in an interactive peripheral display|
|US20100205541 *||Feb 11, 2009||Aug 12, 2010||Jeffrey A. Rapaport||social network driven indexing system for instantly clustering people with concurrent focus on same topic into on-topic chat rooms and/or for generating on-topic search results tailored to user preferences regarding topic|
|US20100249538 *||Mar 24, 2009||Sep 30, 2010||Neurofocus, Inc.||Presentation measure using neurographics|
|US20100249636 *||Sep 30, 2010||Neurofocus, Inc.||Personalized stimulus placement in video games|
|US20100299210 *||Jul 30, 2010||Nov 25, 2010||Promovu, Inc.||System for selectively communicating promotional information to a person|
|US20110029918 *||Jun 28, 2010||Feb 3, 2011||Samsung Electronics Co., Ltd.||Apparatus and method for navigation in digital object using gaze information of user|
|US20110078762 *||Mar 31, 2011||Ebay, Inc.||Mobile or user device authentication and tracking|
|US20110087659 *||Dec 21, 2009||Apr 14, 2011||Prasenjit Dey||Document relevance determining method and computer program|
|US20110161160 *||Jun 30, 2011||Clear Channel Management Services, Inc.||System and method for monitoring audience in response to signage|
|US20110213709 *||Sep 1, 2011||Bank Of America Corporation||Customer and purchase identification based upon a scanned biometric of a customer|
|US20120072291 *||Nov 29, 2011||Mar 22, 2012||Krishna Bharat|
|US20120083675 *||Apr 5, 2012||El Kaliouby Rana||Measuring affective data for web-enabled applications|
|US20120106793 *||May 3, 2012||Gershenson Joseph A||Method and system for improving the quality and utility of eye tracking data|
|US20120173999 *||Sep 13, 2010||Jul 5, 2012||Paolo Invernizzi||Method and apparatus for using generic software applications by means of ocular control and suitable methods of interaction|
|US20120191542 *||Jan 24, 2009||Jul 26, 2012||Nokia Corporation||Method, Apparatuses and Service for Searching|
|US20120290401 *||May 11, 2011||Nov 15, 2012||Google Inc.||Gaze tracking system|
|US20130311924 *||Sep 28, 2012||Nov 21, 2013||Grit Denker||Method, apparatus, and system for modeling passive and active user interactions with a computer system|
|US20130339214 *||Aug 16, 2013||Dec 19, 2013||Trading Technologies International, Inc.||System and Method for Display Management Based on User Attention Inputs|
|US20140085196 *||Apr 19, 2012||Mar 27, 2014||Cisco Technology Inc.||Method and System for Secondary Content Distribution|
|US20140236953 *||Aug 29, 2013||Aug 21, 2014||Jeffrey A. Rapaport||Methods using social topical adaptive networking system|
|US20150049012 *||Jan 23, 2014||Feb 19, 2015||Qualcomm Incorporated||Visual, audible, and/or haptic feedback for optical see-through head mounted display with user interaction tracking|
|US20150127662 *||Nov 7, 2013||May 7, 2015||Yahoo! Inc.||Dwell-time based generation of a user interest profile|
|US20150169048 *||Dec 18, 2013||Jun 18, 2015||Lenovo (Singapore) Pte. Ltd.||Systems and methods to present information on device based on eye tracking|
|US20150261387 *||Mar 17, 2014||Sep 17, 2015||Google Inc.||Adjusting information depth based on user's attention|
|CN103765346A *||Sep 8, 2011||Apr 30, 2014||英特尔公司||Eye gaze based location selection for audio visual playback|
|EP1361504A2 *||May 7, 2003||Nov 12, 2003||Gateway, Inc.||Setting of dwell time for a pointing device|
|EP1607840A1 *||Jun 18, 2004||Dec 21, 2005||Tobii Technology AB||Eye control of computer apparatus|
|EP2202609A3 *||Jun 18, 2004||May 25, 2011||Tobii Technology AB||Eye control of computer apparatus|
|EP2587342A1 *||Oct 28, 2011||May 1, 2013||Tobii Technology AB||Method and system for user initiated query searches based on gaze data|
|WO2012153213A1 *||Apr 19, 2012||Nov 15, 2012||Nds Limited||Method and system for secondary content distribution|
|WO2013036237A1 *||Sep 8, 2011||Mar 14, 2013||Intel Corporation||Eye gaze based location selection for audio visual playback|
|WO2013060892A1 *||Oct 29, 2012||May 2, 2013||Tobii Technology Ab||Method and system for user initiated query searches based on gaze data|
|WO2015034560A1||May 19, 2014||Mar 12, 2015||Tobii Technology Ab||Portable eye tracking device|
|WO2015034561A1||May 19, 2014||Mar 12, 2015||Tobii Technology Ab||Portable eye tracking device|
|WO2015142442A1 *||Feb 12, 2015||Sep 24, 2015||Google Inc.||Adjusting information depth based on user's attention|
|U.S. Classification||715/774, 715/854, 715/831|
|International Classification||G06Q30/02, G06F3/00, G06F3/01|
|Cooperative Classification||G06F3/013, G06Q30/02|
|European Classification||G06Q30/02, G06F3/01B4|
|Feb 25, 1999||AS||Assignment|
Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y
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